To efficiently operate a power transmission and/or distribution system, power must be dynamically distributed according to the changing power demands on the system. Efficient distribution is particularly difficult for those utilities servicing a significant component of large asynchronous loads that start up and shut down abruptly ("non-conforming loads").
To regulate the distribution of power, utilities typically employ automatic generation control systems ("AGCs") which control the distribution of power based on real-time monitoring of system frequency and interchange. When power demand cannot be met by the active generators at a particular utility, power is channeled from other, neighboring utilities. The exchange of power between utilities is called MW interchange.
To anticipate MW interchange, utility operators construct a set of MW interchange schedules based on the predicted needs of the various utilities servicing a region. However, actual MW interchange inevitably diverges from the scheduled levels. The extent to which actual MW interchange diverges from the scheduled MW interchange is typically monitored by each utility's AGC. Specifically, the operating area MW frequency, and the difference between the actual net MW interchange and the scheduled net MW interchange, are used to determine an Area Control Error ("ACE").
For example, ACE may be calculated according to Equation 1, where AI is the actual instantaneous operating area MW interchange, SI is the scheduled instantaneous operating area MW interchange, AF is the actual instantaneous operating area frequency, SF is the scheduled instantaneous operating area frequency, and FB is an operating area frequency bias parameter in MW/0.1 Hz. EQU ACE=(AI-SI)-10FB(AF-SF) (1)
An AGC could be configured to minimize or eliminate the Area Control Error by controlling the output of the generators of a utility in an attempt to exactly meet the power demands within the utility's area while providing any additional power for the scheduled MW interchange. However, the cost of chasing transient demand fluctuations is substantial. The waste caused by the pursuit of short-term demand fluctuations is further compounded when generators are activated or deactivated by operators in response to such fluctuations.
Thus, increasing the output levels of generators to meet an unanticipated load increase is only justified when the demand will be sustained for a significant period of time. Likewise, the output level of a generator should not be decreased in response to a drop in demand if it can be anticipated that the decrease in demand is only transient.
It is therefore desirable to recognize and distinguish between demand changes that will be sustained and those which will be transient. However, it is often difficult to distinguish between load disturbances indicative of sustained demand changes, load disturbances indicative of transient demand changes, and noise, such as transient power spikes. For example, noise can effectively mask significant non-zero centered load disturbances.
Filtering techniques may be employed to minimize noise, and thus make accurate disturbance classification more feasible. However, filtering tends to induce delays which adversely impact controller actions.
Attempts to automatically predict sustained demand changes based on load disturbance readings have only been moderately successful. For example, error adaptive control computers have been used to classify load disturbances using pre-specified classification functions, such as those disclosed in U.S. Pat. No. 3,633,009 issued to Green et al. While such methods can be tuned to detect one class of disturbances with accuracy, they do not perform optimally for other classes of disturbances. Further, such methods require prior knowledge of the statistical properties of the relevant processes, and are incapable of detecting new, unanticipated classes of disturbances.
As power transmission and/or distribution systems are likely to encounter load disturbances from a wide range of classes, many of which classes may not have been anticipated, it is clearly desirable to provide a power control system capable of quickly and accurately classifying disturbances belonging to a wide variety of classes, including unanticipated classes. It is further desirable to provide a power control system that automatically controls the output levels of generators in response to a signal indicative of the class of detected load disturbances.